matplotlib
diff --git a/‎lib/matplotlib/image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/image.py
+3-3Lines changed: 3 additions & 3 deletions b/‎lib/matplotlib/image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/image.py
+3-3Lines changed: 3 additions & 3 deletions
diff --git a/‎lib/matplotlib/tests/test_image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_image.py
+18-1Lines changed: 18 additions & 1 deletion b/‎lib/matplotlib/tests/test_image.py
Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_image.py
+18-1Lines changed: 18 additions & 1 deletion
@@ -532,9 +532,9 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                 # we have re-set the vmin/vmax to account for small errors
                 # that may have moved input values in/out of range
                 s_vmin, s_vmax = vrange
-                if isinstance(self.norm, mcolors.LogNorm):
-                    if s_vmin < 0:
-                        s_vmin = max(s_vmin, np.finfo(scaled_dtype).eps)
+                if isinstance(self.norm, mcolors.LogNorm) and s_vmin <= 0:
+                    # Don't give 0 or negative values to LogNorm
+                    s_vmin = np.finfo(scaled_dtype).eps
                 with cbook._setattr_cm(self.norm,
                                        vmin=s_vmin,
                                        vmax=s_vmax,
 
@@ -1234,7 +1234,7 @@ def test_imshow_quantitynd():
 
 
 @check_figures_equal(extensions=['png'])
-def test_huge_range_log(fig_test, fig_ref):
+def test_huge_range_log_negative(fig_test, fig_ref):
     data = np.full((5, 5), -1, dtype=np.float64)
     data[0:2, :] = 1E20
 
@@ -1252,6 +1252,23 @@ def test_huge_range_log(fig_test, fig_ref):
                    interpolation='nearest', cmap=cmap)
 
 
+@check_figures_equal(extensions=['png'])
+def test_huge_range_log(fig_test, fig_ref):
+    data = np.full((5, 5), 1, dtype=np.float64)
+    data[0:2, :] = 1E20
+
+    ax = fig_test.subplots()
+    im = ax.imshow(data, norm=colors.LogNorm(vmin=1, vmax=data.max()),
+                   interpolation='nearest', cmap='viridis')
+
+    data = np.full((5, 5), 1, dtype=np.float64)
+    data[0:2, :] = 1000
+
+    ax = fig_ref.subplots()
+    im = ax.imshow(data, norm=colors.Normalize(vmin=1, vmax=data.max()),
+                   interpolation='nearest', cmap='viridis')
+
+
 @check_figures_equal()
 def test_spy_box(fig_test, fig_ref):
     # setting up reference and test